Concentration monitoring method and system, storage medium and electronic device

Abstract

This invention provides a method and system for monitoring attention, a storage medium, and an electronic device, comprising the following steps: acquiring electroencephalogram (EEG) signals of a subject in a focused state and an unfocused state; generating an attention monitoring model corresponding to the subject based on the EEG signals; and acquiring an attention level index of the subject based on the attention monitoring model. The attention monitoring method and system, storage medium, and electronic device of this invention achieve attention monitoring through the subject's attention monitoring model, greatly improving the accuracy of attention monitoring.

Description

Technical Field

[0001] This invention relates to the technical field of attention monitoring, and in particular to an attention monitoring method and system, storage medium and electronic device. Background Technology

[0002] Electroencephalogram (EEG) signals can be divided into two main categories: one is called time-related EEG, also known as evoked EEG, which is the fluctuation of EEG signals generated by the brain in response to stimulation; the other is called spontaneous EEG, which, in contrast to evoked EEG signals, refers to regular potential signals generated spontaneously by the brain.

[0003] The study of electroencephalogram (EEG) signals has a history of nearly eighty years, with significant applications in science, technology, military, entertainment, virtual reality, and many other fields. Particularly in clinical medicine, as a crucial indicator of brain function, it has been, is, and will continue to be valuable in clinical diagnosis and scientific research. Current research shows that the frequency range of EEG recordings analyzed in clinical settings is roughly 1.0–100 Hz, with the main frequency bands converging between 0.3–30 Hz. These can be divided into four important bands: δ (0.5–4 Hz), θ (4–8 Hz), α (8–12 Hz), and β (12–22 Hz), corresponding to delta, theta, alpha, and beta rhythms, respectively. Their frequency range and waveform diagrams are shown below. Figure 1 As shown.

[0004] Electroencephalogram (EEG) signals generate a rich variety of frequencies, with different wavebands associated with different states of thought or activity. For example, beta waves appear when a person is mentally stressed or emotionally excited, while theta waves are more prominent when a person is fatigued or depressed. It is evident that EEG signals act as an indicator of brain function, displaying different characteristics at different ages, in different physical and psychological states. The significance of further classifying EEG signals is self-evident. This is not only closely related to human mental and physical health but also lays the theoretical foundation for the development of brainwave control devices.

[0005] According to neuroscience research, the correlation between attentional states and the rhythm of electroencephalogram (EEG) signals is widely accepted. In 1985, William et al. found that the alpha and beta bands in EEG signals reflect a subject's level of attention. When entering a state of focus, the energy of the alpha band decreases, while the energy of the beta band increases. Numerous other studies have investigated changes in the energy ratios between beta, alpha, and other different bands caused by attention. Overall, many studies consider increased activity in high-frequency bands like beta to be an indicator of attentional arousal. Other studies have shown that a decrease in the energy ratio of theta and beta, and a decrease in the energy of alpha and theta, also indicate a higher level of focus.

[0006] However, using the energy ratio of different frequency bands of EEG signals as an indicator of attention detection has a significant limitation on its practical application. Specifically, the effectiveness of this indicator varies from person to person. For some subjects, it often fails to accurately measure attention levels. To address this issue, some researchers have proposed combining multiple indicators to measure attention levels, such as weighted averaging of β / α and β / θ indicators to obtain a new indicator for detecting attention levels. While this method of combining multiple indicators has addressed the accuracy issue of attention detection to some extent, since each indicator is still a traditional frequency band energy indicator, its accuracy and stability in detecting attention levels remain insufficient. Summary of the Invention

[0007] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a focus monitoring method and system, storage medium and electronic device, which realizes focus monitoring through the focus monitoring model of the subject, and greatly improves the accuracy of focus monitoring.

[0008] In a first aspect, the present invention provides a method for monitoring attention, comprising the following steps: acquiring electroencephalogram (EEG) signals of a subject in a focused state and an unfocused state; generating an attention monitoring model corresponding to the subject based on the EEG signals; and acquiring an attention level index of the subject based on the attention monitoring model.

[0009] In one implementation of the first aspect, generating a focus monitoring model corresponding to the subject based on the electroencephalogram (EEG) signal includes the following steps:

[0010] The weights of the subject's energy for different frequencies of EEG signals are obtained based on the EEG signals.

[0011] The attention monitoring model is constructed, which is used to calculate the attention level index based on the energy and corresponding weight of the EEG signals of different frequencies of the subject.

[0012] In one implementation of the first aspect, obtaining the weights of the subject's energy for different frequencies of EEG signals based on the EEG signals includes the following steps:

[0013] Obtain the energy ratio of EEG signals corresponding to focused and unfocused states at different frequencies;

[0014] The weights of the energy of EEG signals at different frequencies are obtained by weighting the signal by the formula |1 - energy ratio|, where || represents the absolute value.

[0015] In one implementation of the first aspect, calculating the attention level index based on the attention model according to the energy and corresponding weights of the subject's EEG signals at different frequencies includes:

[0016] according to The focus level index is calculated, where + and - represent the frequency bands of energy increase and energy decrease of the EEG signal in the focused state compared to the non-focused state, respectively; g(w) and f(w) represent the weights corresponding to the energy of the EEG signal at frequency w, respectively; and p(w) represents the energy of the EEG signal at frequency w.

[0017] In one implementation of the first aspect, obtaining the subject's attention level index based on the attention monitoring model includes the following steps:

[0018] Acquire the subject's electroencephalogram (EEG) signal to be tested;

[0019] The attention level index corresponding to the EEG signal to be tested is obtained based on the attention monitoring model.

[0020] In one implementation of the first aspect, the method further includes denoising the EEG signal to generate a focus monitoring model corresponding to the subject based on the denoised EEG signal.

[0021] In one implementation of the first aspect, a reminder message is also issued when the focus level index is less than a preset threshold.

[0022] Secondly, the present invention provides a focus monitoring system, including an acquisition module, a generation module and a monitoring module;

[0023] The acquisition module is used to acquire the electroencephalogram (EEG) signals of the subject in a focused state and an unfocused state;

[0024] The generation module is used to generate a focus monitoring model corresponding to the subject based on the electroencephalogram (EEG) signal;

[0025] The monitoring module is used to obtain the subject's attention level index based on the attention monitoring model.

[0026] Thirdly, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described attention monitoring method.

[0027] Fourthly, the present invention provides an electronic device, comprising: a processor and a memory;

[0028] The memory is used to store computer programs;

[0029] The processor is used to execute the computer program stored in the memory to cause the electronic device to perform the attention monitoring method described above.

[0030] Fifthly, the present invention provides a focus monitoring system, including an electroencephalogram (EEG) signal acquisition device and the aforementioned electronic device;

[0031] The EEG signal acquisition device is used to acquire EEG signals and send the EEG signals to the electronic device.

[0032] As described above, the attention monitoring method and system, storage medium, and electronic device of the present invention have the following beneficial effects:

[0033] (1) By collecting EEG data of subjects in focused and unfocused states, the weights of the energy of EEG signals in different frequencies are obtained, thereby training a focus monitoring model, and using the focus monitoring model to monitor the focus of subjects.

[0034] (2) It takes into account the effect of the energy of EEG signals of different frequencies within the frequency band on the level of concentration, thus improving the accuracy of concentration monitoring.

[0035] (3) The differences in attention monitoring models between people are taken into account, which improves the usability of attention monitoring. Attached Figure Description

[0036] Figure 1 The diagram shows a frequency band division of electroencephalogram (EEG) signals in one embodiment of the prior art.

[0037] Figure 2 The flowchart shown is an embodiment of the attention monitoring method of the present invention;

[0038] Figure 3 This is a schematic diagram showing the relationship between the energy ratio and frequency of EEG signals in a focused state and a non-focused state in one embodiment.

[0039] Figure 4 The diagram shown is a structural schematic of the attention monitoring system of the present invention in one embodiment.

[0040] Figure 5 The diagram shown is a structural schematic of the electronic device of the present invention in one embodiment;

[0041] Figure 6 The diagram shown is a structural schematic of another embodiment of the attention monitoring system of the present invention. Detailed Implementation

[0042] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0043] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0044] The following embodiments of the present invention provide a focus monitoring method that can be applied to electronic devices. The electronic devices described in this invention may include mobile phones with wireless charging capabilities, tablet computers, laptops, wearable devices, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), etc. The embodiments of the present invention do not impose any limitations on the specific type of electronic device.

[0045] For example, the electronic device may be a station (STAION, ST) in a WLAN with wireless charging capability, a cellular phone, cordless phone, Session Initiation Protocol (SIP) phone, Wireless Local Loop (WLL) station, Personal Digital Assistant (PDA) device, handheld device with wireless charging capability, computing device or other processing device, computer, laptop computer, handheld communication device, handheld computing device, and / or other devices for communication over a wireless system, as well as next-generation communication systems, such as mobile terminals in 5G networks, mobile terminals in future evolved Public Land Mobile Networks (PLMNs), or mobile terminals in future evolved Non-terrestrial Networks (NTNs).

[0046] For example, the electronic device can communicate with networks and other devices wirelessly. The wireless communication can use any communication standard or protocol, including but not limited to Global System for Mobile Communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), BT, GNSS, WLAN, NFC, FM, and / or IR technologies. The GNSS can include Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), BeiDou Navigation Satellite System (BDS), Quasi-Zenith Satellite System (QZSS), and / or Satellite Based Augmentation Systems (SBAS).

[0047] The technical solutions of the present invention will now be described in detail with reference to the accompanying drawings.

[0048] like Figure 2 As shown, in one embodiment, the attention monitoring method of the present invention includes the following steps:

[0049] Step S1: Obtain the electroencephalogram (EEG) signals of the subject in a focused state and an unfocused state.

[0050] Specifically, the subject wears an EEG signal acquisition device, which induces the subject to enter both focused and unfocused states. The EEG signal acquisition device collects the subject's EEG signals during the focused and unfocused states and provides these signals to the electronic device of this invention.

[0051] To improve the stability of subject attention monitoring, the amount of EEG signals can be increased. For example, EEG signals can be collected from subjects throughout an entire class period. The advantage of this is that subsequent attention monitoring results will be more stable, but the trade-off is a significant increase in time consumption. Therefore, an appropriate amount of EEG data should be selected based on the specific application scenario.

[0052] Step S2: Generate a focus monitoring model corresponding to the subject based on the electroencephalogram (EEG) signal.

[0053] like Figure 3 As shown, the energy ratio of EEG signals in focused and unfocused states varies with frequency. Furthermore, the energy ratio differs at different frequencies across the entire frequency band. Therefore, it can be concluded that within the same frequency band, the energy ratio of EEG signals at different frequencies has different effects on attention monitoring. This invention constructs an attention monitoring model based on these characteristics.

[0054] Specifically, generating the attention monitoring model corresponding to the subject based on the electroencephalogram (EEG) signals includes the following steps:

[0055] 21) Based on the EEG signals, obtain the weights of the subject’s energy for EEG signals of different frequencies.

[0056] First, the energy ratio of EEG signals corresponding to focused and unfocused states at different frequencies is obtained. Then, the weights of the energy of EEG signals at different frequencies are obtained according to the formula: weight = |1 - energy ratio|, where || represents the absolute value.

[0057] 22) Construct the attention monitoring model, which is used to calculate the attention level index based on the energy and corresponding weight of the EEG signals of different frequencies of the subject.

[0058] The attention monitoring model is used to calculate the weighted integral value of the energy and corresponding weights of EEG signals at different frequencies as the attention level indicator. That is, based on... The focus level index is calculated, where + and - represent the frequency bands of the EEG signal where the energy increases and decreases during a focused state compared to a non-focused state, respectively. Figure 3 The frequency ranges corresponding to the portions of the curve above and below 1, g(w) and f(w) represent the weights corresponding to the energy of the EEG signal at frequency w, respectively, and p(w) represents the energy of the EEG signal at frequency w.

[0059] Preferably, the attention monitoring method of the present invention further includes denoising the electroencephalogram (EEG) signal to generate an attention monitoring model corresponding to the subject based on the denoised EEG signal, thereby improving the accuracy of attention monitoring.

[0060] Step S3: Obtain the subject's attention level index based on the attention monitoring model.

[0061] Specifically, after generating the attention monitoring model, attention monitoring can be performed on the subject. First, the subject's electroencephalogram (EEG) signal to be tested is acquired; then... The attention level index corresponding to the EEG signal to be tested can then be obtained.

[0062] In one embodiment, the attention monitoring method of the present invention further includes issuing a reminder message when the attention level index is less than a preset threshold. For example, in a classroom, when a student's attention level index is less than the preset threshold, a reminder message can be sent to the student or teacher to facilitate timely adjustment and improve learning focus.

[0063] The scope of protection of the attention monitoring method described in this embodiment is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principles of this invention is included within the scope of protection of this invention.

[0064] This invention also provides a focus monitoring system, which can implement the focus monitoring method described in this invention. However, the implementation device of the focus monitoring system described in this invention includes, but is not limited to, the structure of the focus monitoring system listed in this embodiment. Any structural modifications and substitutions of the prior art made in accordance with the principles of this invention are included within the protection scope of this invention.

[0065] like Figure 4 As shown, in one embodiment, the attention monitoring system of the present invention includes an acquisition module 41, a generation module 42, and a monitoring module 43.

[0066] The acquisition module 41 is used to acquire the electroencephalogram (EEG) signals of the subject in a focused state and an unfocused state.

[0067] The generation module 42 is connected to the acquisition module 41 and is used to generate a focus monitoring model corresponding to the subject based on the electroencephalogram (EEG) signal.

[0068] The monitoring module 43 is connected to the generation module 42 and is used to obtain the subject's attention level index based on the attention monitoring model.

[0069] The structure and principle of the acquisition module 41, the generation module 42 and the monitoring module 43 correspond one-to-one with the steps in the attention monitoring method described above, so they will not be repeated here.

[0070] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of apparatuses or modules or units may be electrical, mechanical, or other forms.

[0071] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of the present invention, depending on actual needs. For example, the functional modules / units in the various embodiments of the present invention may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0072] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0073] This invention also provides a computer-readable storage medium. Those skilled in the art will understand that all or part of the steps in the attention monitoring method of the above embodiments can be implemented by a program instructing a processor. The program can be stored in a computer-readable storage medium, which is a non-transitory medium, such as random access memory, read-only memory, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disk, and any combination thereof. The storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. This available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0074] This invention also provides an electronic device. The electronic device includes a processor and a memory.

[0075] The memory is used to store computer programs.

[0076] The memory includes various media capable of storing program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card, or optical disk.

[0077] The processor is connected to the memory and is used to execute the computer program stored in the memory so that the electronic device performs the attention monitoring method described above.

[0078] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0079] like Figure 5As shown, the electronic device of the present invention is embodied in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: one or more processors or processing units 51, a memory 52, and a bus 53 connecting different system components (including the memory 52 and the processing unit 51).

[0080] Bus 53 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0081] Electronic devices typically include a variety of computer-readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, and removable and non-removable media.

[0082] Memory 52 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 521 and / or cache memory 522. The electronic device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 523 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 5 Not shown; usually referred to as a "hard drive"). Although Figure 5 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 53 via one or more data media interfaces. Memory 52 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0083] A program / utility 524 having a set (at least one) of program modules 5241 may be stored, for example, in memory 52. ​​Such program modules 5241 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 5241 typically perform the functions and / or methods described in the embodiments of the present invention.

[0084] The electronic device can also communicate with one or more external devices (e.g., keyboard, pointing device, display, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., network interface card, modem, etc.). This communication can be performed through input / output (I / O) interface 54. Furthermore, the electronic device can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 55. Figure 5 As shown, network adapter 55 communicates with other modules of the electronic device via bus 53. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0085] like Figure 6 As shown, in one embodiment, the attention monitoring system of the present invention includes an electroencephalogram (EEG) signal acquisition device 61 and the aforementioned electronic device 62.

[0086] The EEG signal acquisition device 61 is used to acquire EEG signals and transmit the EEG signals to the electronic device 62. The EEG signal acquisition device 61 and the electronic device 62 transmit signals via wired or wireless means.

[0087] In summary, the attention monitoring method, system, storage medium, and electronic device of the present invention acquire the weights of the energy of EEG signals at different frequencies by collecting EEG data from subjects in focused and unfocused states, thereby training an attention monitoring model, and using the attention monitoring model to monitor the subject's attention. It takes into account the influence of the energy of EEG signals at different frequencies within the frequency band on attention levels, improving the accuracy of attention monitoring; and considers the differences in attention monitoring models between individuals, improving the usability of attention monitoring. Therefore, the present invention effectively overcomes the various shortcomings of the prior art and has high industrial application value.

[0088] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for monitoring attention, characterized in that, Includes the following steps: Acquire electroencephalogram (EEG) signals from subjects in focused and unfocused states; Based on the electroencephalogram (EEG) signals, a focus monitoring model corresponding to the subject is generated; The attention level index of the subject is obtained based on the attention monitoring model. Based on the aforementioned attention model, attention level indicators are calculated according to the energy and corresponding weights of the subject's EEG signals at different frequencies, including: Based on focus The focus level index is calculated, where + and - represent the frequency bands of energy increase and energy decrease of the EEG signal in the focused state compared to the non-focused state, respectively; g(w) and f(w) represent the weights corresponding to the energy of the EEG signal at frequency w in the frequency bands of energy increase and energy decrease in the focused state compared to the non-focused state, respectively; and p(w) represents the energy of the EEG signal at frequency w.

2. The attention monitoring method according to claim 1, characterized in that, Generating a focus monitoring model for the subject based on the electroencephalogram (EEG) signals includes the following steps: The weights of the subject's energy for different frequencies of EEG signals are obtained based on the EEG signals. The attention monitoring model is constructed, which is used to calculate the attention level index based on the energy and corresponding weights of the EEG signals of different frequencies of the subject.

3. The attention monitoring method according to claim 2, characterized in that, Obtaining the weights of the subject's energy for different frequencies of EEG signals based on the EEG signals includes the following steps: Obtain the energy ratio of EEG signals corresponding to focused and unfocused states at different frequencies; The weights of the energy of EEG signals at different frequencies are obtained by weighting the signal by the formula |1 - energy ratio|, where || represents the absolute value.

4. The attention monitoring method according to claim 1, characterized in that, Obtaining the subject's attention level index based on the attention monitoring model includes the following steps: Acquire the subject's electroencephalogram (EEG) signal to be tested; The attention level index corresponding to the EEG signal to be tested is obtained based on the attention monitoring model.

5. The attention monitoring method according to claim 1, characterized in that, It also includes issuing a reminder message when the focus level indicator is less than a preset threshold.

6. A focus monitoring system, characterized in that, It includes an acquisition module, a generation module, and a monitoring module; The acquisition module is used to acquire the electroencephalogram (EEG) signals of the subject in a focused state and an unfocused state; The generation module is used to generate a focus monitoring model corresponding to the subject based on the electroencephalogram (EEG) signal. The monitoring module is used to obtain the subject's attention level index based on the attention monitoring model; Based on the aforementioned attention model, attention level indicators are calculated according to the energy and corresponding weights of the subject's EEG signals at different frequencies, including: Based on focus The focus level index is calculated, where + and - represent the frequency bands of energy increase and energy decrease of the EEG signal in the focused state compared to the non-focused state, respectively; g(w) and f(w) represent the weights corresponding to the energy of the EEG signal at frequency w in the frequency bands of energy increase and energy decrease in the focused state compared to the non-focused state, respectively; and p(w) represents the energy of the EEG signal at frequency w.

7. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the attention monitoring method as described in any one of claims 1 to 5.

8. An electronic device, characterized in that, include: Processor and memory; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory to cause the electronic device to perform the attention monitoring method according to any one of claims 1 to 5.

9. A focus monitoring system, characterized in that, It includes an electroencephalogram (EEG) signal acquisition device and the electronic device as described in claim 8; the EEG signal acquisition device is used to acquire EEG signals and send the EEG signals to the electronic device.

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